{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Paddle指导三维室内空气流动的网格自适应细化"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **一、项目介绍**\n",
    "\n",
    "### 1. 相关背景\n",
    "计算流体力学（CFD）是21世纪流体力学领域的重要技术之一，使用数值方法在计算机中对流体力学的控制方程进行求解，从而可预测流场的流动。目前有多种成熟的CFD软件，比如FLUENT、Star-CD、OpenFoam、CFX等。为了求解流体力学的控制方程，一个必要的前提是有适合数值方法的离散网格。生成离散网格的软件也有多种，比如ICEM、GAMBIT、ANSYS、Star-CD等。离散网格的质量（Quality）是影响CFD求解的关键因素。但是在传统的CFD流程中，离散网格的生成仅有一些指导经验。为了生成一个高质量的离散网格，往往需要对CFD求解结果进行网格敏感性分析（Mesh Sensitiviy Study）。这是一个耗时且无法跳过的过程。\n",
    "\n",
    "近年来基于物理信息约束神经元网络（PINNs）的方法在流体力学领域较为流行。PINN的特色是在神经元网络的损失函数（Loss Function）里包含流体力学的控制方程，使得神经元网络可以代替CFD的求解过程。对比CFD软件，PINNs的求解速度较快，一部分是因为PINNs对CFD流程的简化，另一部分是因为PINNs的计算是在GPU上进行。但是，目前PINN求解精度还有待提高。\n",
    "\n",
    "### 2. 功能目标\n",
    "本课题的目的是基于PINNs进行CFD离散网格优化，即并不采用PINN代替高精度的CFD求解器，而是用PINNs的求解速度快以及其具备一定的求解精度的特点，加快寻找最优的离散网格，从而缩短整体CFD流程的速度。本质上，本课题是为了验证一个假说，即高质量的离散网格，也对应相对高精度的PINN。\n",
    "\n",
    "### 3. 意义\n",
    "本课题的意义是探索区别于传统方式生成网格的技术，验证PINNs进行CFD离散网格优化的可行性，为工业应用计算软件提供一个基于机器学习的高质量网格生成与细化的新路径。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 二、设计方案与实现流程\n",
    "\n",
    "### 1. 网格优化总体方案\n",
    "\n",
    "我们所提出的基于PINNs对网格进行优化的具体方案示意如图所示。Level表示优化的层级，Points/Nodes表示训练点集或者网格的节点，Mesh代表三角形或者四面体网格，CFD solutions为传统CFD得到的参考解。注意，这里的CFD solution是否调用是可自由选择的，故在图中使用虚线来表示，可以根据实际训练情况灵活地选择是否使用CFD数据来进行无监督学习（无CFD数据)或监督学习（有CFD数据)。\n",
    "\n",
    "**值得一提的是，本案例我们对优化方案进行了适当地改动。即仅在模型预测阶段使用基于物理的PINNs，而在模型训练阶段使用纯数据驱动的方式。这种方案不管在效率还是精度上都优于原始PINNs的优化方式（训练和预测都加入物理信息）。** 因为PINNs在流场各物理量的数据都充分已知的情况下进行监督学习时，加入物理信息约束（Physics-informed constraint）反倒会使得CFD数据的损失和物理信息的损失这两类约束相互竞争，最终得到更加偏离原CFD的解。同时物理信息约束也会大大增加神经网络的训练时间。基于以上理由，我们对原有方案进行了适当调整。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/0e1e6e2ea930489b9b2a2af2cf6c2be77530ff2a4323426cb0b157c898e93e56)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 环境配置\n",
    "\n",
    "1. 该项目需要结合CFD数据集进行PINNs或FCNN模型的训练和预测，我们选择使用以paddle为后端的科学计算库DeepXDE。\n",
    "2. 对某些网格文件（如.msh或.vtk）进行读取和写入的meshio库。\n",
    "3. 采用scipy、meshpy和pyvtk库对三维散点集执行Delaunay四面体化生成非结构有限元网格。 \n",
    "4. 四面体网格可视化交互使用pyvista和panel库。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "**以下为可安装在持久化路径中的库，安装一次后无需再次安装**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:13:10.605668Z",
     "iopub.status.busy": "2023-11-29T08:13:10.604531Z",
     "iopub.status.idle": "2023-11-29T08:13:10.610256Z",
     "shell.execute_reply": "2023-11-29T08:13:10.609104Z",
     "shell.execute_reply.started": "2023-11-29T08:13:10.605613Z"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "# 持久化路径进行持久化安装\n",
    "!mkdir /home/aistudio/external-libraries\n",
    "# 机器学习库(自动识别paddle作为后端)\n",
    "!pip install deepxde -t /home/aistudio/external-libraries\n",
    "# 网格文件读写库\n",
    "!pip install meshio -t /home/aistudio/external-libraries\n",
    "# 四面体网格生成\n",
    "!pip install meshpy pyvtk -t /home/aistudio/external-libraries\n",
    "# 网格可视化交互\n",
    "!pip install pyvista panel -t /home/aistudio/external-libraries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**只需更新一些必要的库**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:13:10.612720Z",
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     "shell.execute_reply": "2023-11-29T08:13:18.416369Z",
     "shell.execute_reply.started": "2023-11-29T08:13:10.612689Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://mirror.baidu.com/pypi/simple/, https://mirrors.aliyun.com/pypi/simple/, https://pypi.tuna.tsinghua.edu.cn/simple/\r\n",
      "Requirement already satisfied: numpy in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (1.21.6)\r\n",
      "Requirement already satisfied: scipy in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (1.7.3)\r\n",
      "Requirement already satisfied: matplotlib in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (3.5.3)\r\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from matplotlib) (3.0.9)\r\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from matplotlib) (2.8.2)\r\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from matplotlib) (0.10.0)\r\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from matplotlib) (4.38.0)\r\n",
      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from matplotlib) (8.2.0)\r\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from matplotlib) (1.1.0)\r\n",
      "Requirement already satisfied: packaging>=20.0 in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from matplotlib) (21.3)\r\n",
      "Requirement already satisfied: six in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from cycler>=0.10->matplotlib) (1.16.0)\r\n",
      "Requirement already satisfied: setuptools in /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib) (41.4.0)\r\n",
      "\r\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.1.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\r\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "!pip install --upgrade numpy scipy matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:13:18.419724Z",
     "iopub.status.busy": "2023-11-29T08:13:18.419205Z",
     "iopub.status.idle": "2023-11-29T08:13:18.425182Z",
     "shell.execute_reply": "2023-11-29T08:13:18.424033Z",
     "shell.execute_reply.started": "2023-11-29T08:13:18.419686Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# 每次环境(kernel)启动时导入持久路径的库: \n",
    "import sys \n",
    "sys.path.append('/home/aistudio/external-libraries')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:13:18.428046Z",
     "iopub.status.busy": "2023-11-29T08:13:18.427645Z",
     "iopub.status.idle": "2023-11-29T08:13:22.662429Z",
     "shell.execute_reply": "2023-11-29T08:13:22.660965Z",
     "shell.execute_reply.started": "2023-11-29T08:13:18.428015Z"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using backend: paddle\r\n",
      "Other available backends: tensorflow.compat.v1, tensorflow, pytorch, jax.\r\n",
      "paddle supports more examples now and is recommended.\r\n",
      " \r\n"
     ]
    }
   ],
   "source": [
    "# 测试导入所需的库\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import deepxde as dde\n",
    "import meshio\n",
    "from scipy.spatial import Delaunay\n",
    "from meshpy.tet import MeshInfo, build, Options\n",
    "import pyvista as pv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. CFD模拟场景：室内空气流动（Re=300000）\n",
    "\n",
    "场景描述如图所示，一个3$m$ x 3$m$ x 3$m$的立方体代表了房间，房间的一个**侧面墙上有一个朝室内吹气的矩形风口**，房间的**顶部正中间有个圆形的出风口**。其他边界均为壁面。进风口为速度入口，速度为1$m/s$，出风口为0压力出口。不考虑重力和传热。气体为不可压缩空气，密度为1.2$kg/m^3$，运动粘性系数为$1.8e^{-5} Pa·s$。该流动的特征雷诺数为$Re=UD/v=300000$，其中$U$为来流速度，$D$为特征长度（我们选取立方体的边长为特征长度），$v$为运动粘性系数。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/371df0c521c74a3e8043732f8bb4b893ed18f4ab011b4688be477d67abf43fb0)\n",
    "\n",
    "\n",
    "由于求解区域的几何形状和流动都关于Z轴的中心面对称，因此计算得到的流场在理论上应该关于该面是对称的。而初始网格的不对称性会导致求解流场不对称，从而在后续自适应加密时也会产生不对称的网格，反过来增加流场的不对称性。**因此我们选择将Z轴的中心面设置为对称边界，这样只需求解原计算域一半的区域。一来可以强制网格和流场都严格对称，二来可以减少CFD和机器学习训练的计算量。** 流场求解区域如下图所示。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/cc975529813849d9b47d1d1d7562d5ec6fd1315999f24eeeafbac716dc7fb888)\n",
    "\n",
    "\n",
    "我们使用**ANSYS Fluent**生成一半区域的初始四面体非结构网格（1479 nodes，7010 cells）并对该场景进行模拟。湍流模型选用SST K-omega。模拟结果如下图所示：\n",
    "\n",
    "#### Z 轴中心面流场的速度幅值、压力、速度$u$和速度$v$\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/c55820d440fd4a67902065288dbb7c15c58613e43c1149c482ce8051157e912e)\n",
    "\n",
    "后续我们使用ANSYS Fluent来求解初始网格（Level1）以及不同优化阶段的网格（Level2 - n）的流场，所用求解器以及相关设置均固定。\n",
    "Fluent求解得到的数据同时也提供给机器学习模型进行纯数据驱动的监督学习。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在每个level的子文件夹**1_Fluent_results**内运行以下代码可**读取室内空气流动的Fluent求解结果**，并保存成供模型训练的numpy数组："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2023-11-29T08:13:22.663966Z",
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     "shell.execute_reply": "2023-11-29T08:13:23.165194Z",
     "shell.execute_reply.started": "2023-11-29T08:13:22.664672Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/aistudio/work/room/level1/1_Fluent_results\r\n",
      "[[ 1.00000000e+00 -0.00000000e+00  2.55000000e+00 ...  5.92269579e-01\r\n",
      "  -5.13170241e-16  5.17901474e-16]\r\n",
      " [ 2.00000000e+00 -1.70000000e-16  2.63983900e+00 ...  0.00000000e+00\r\n",
      "   0.00000000e+00  0.00000000e+00]\r\n",
      " [ 3.00000000e+00  6.99740000e-02  2.55474100e+00 ...  4.64265252e-01\r\n",
      "  -4.05889401e-02  4.16069112e-03]\r\n",
      " ...\r\n",
      " [ 1.47700000e+03  2.20620000e+00  3.00000000e+00 ...  0.00000000e+00\r\n",
      "   0.00000000e+00  0.00000000e+00]\r\n",
      " [ 1.47800000e+03  2.21466600e+00  2.83876600e+00 ...  4.45677249e-01\r\n",
      "   2.30592012e-02  0.00000000e+00]\r\n",
      " [ 1.47900000e+03  2.09473800e+00  3.00000000e+00 ...  0.00000000e+00\r\n",
      "   0.00000000e+00  0.00000000e+00]]\r\n",
      "\r\n",
      "level1网格节点个数: 1479\r\n",
      "\r\n",
      "Fluent数据保存完成\r\n",
      "/home/aistudio\r\n"
     ]
    }
   ],
   "source": [
    "%cd work/room/level1/1_Fluent_results/\n",
    "!python read_fluent_results.py\n",
    "%cd /home/aistudio/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. 读取Fluent网格节点并重新生成四面体网格\n",
    "\n",
    "官方提供的网格为多面体网格。因此，我们将Fluent生成的非结构四面体网格导出为.msh格式的文件。该网格文件可被meshio、gmsh、fluent、workbench等通用软件读取。接下来，我们通过`meshio`来实现从Fluent导出的网格文件（.msh）的三维节点坐标读取，并使用python的非结构网格生成库`scipy`和`meshpy`来实现Delaunay四面体化将其构建为非结构网格。对于室内流动立方体的网格生成，不需要考虑任何内部边界约束，因此四面体化过程相对简单。**后续所有的从坐标点生成四面体网格、或者对原网格进行加密的步骤均基于此算法。**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Delaunay 四面体化：\n",
    "\n",
    "在level1的0_Mesh_files文件夹中直接运行read_mesh_and_remesh.py可对所提取网格节点进行Delaunay四面体化生成网格。代码和生成结果如下所示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2023-11-29T08:13:25.211742Z",
     "shell.execute_reply.started": "2023-11-29T08:13:23.169015Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/aistudio/work/room/level1/0_Mesh_files\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m4\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
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      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m11\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m11\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m11\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m11\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m11\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m11\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m316\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Zone specification not supported yet. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m38\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m60\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Unknown index \u001b[0m\u001b[1;33m73\u001b[0m\u001b[33m. Skipping.\u001b[0m\r\n",
      "从fluent网格中读取节点数： 1592\r\n",
      "删除重复点后剩余节点数： 1479\r\n",
      "\r\n",
      "Delaunay四面体化完成\r\n",
      "\r\n",
      "New mesh infos:\r\n",
      "Nodes: 1479\r\n",
      "Cells: 7010\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Appending zeros to replace the missing physical tag data.\u001b[0m\r\n",
      "\u001b[1;33mWarning:\u001b[0m\u001b[33m Appending zeros to replace the missing geometrical tag data.\u001b[0m\r\n",
      "网格已成功保存为vtk和msh文件: room_tet_remesh.vtk room_tet_remesh.msh\r\n"
     ]
    }
   ],
   "source": [
    "%cd /home/aistudio/work/room/level1/0_Mesh_files/\n",
    "!python -W ignore read_mesh_and_remesh.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**运行以下代码进行网格可视化交互(可鼠标拖动查看网格)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:13:25.215724Z",
     "iopub.status.busy": "2023-11-29T08:13:25.214873Z",
     "iopub.status.idle": "2023-11-29T08:13:32.323580Z",
     "shell.execute_reply": "2023-11-29T08:13:32.322537Z",
     "shell.execute_reply.started": "2023-11-29T08:13:25.215682Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
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       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
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       "\n",
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       "        if (callback != null)\n",
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       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, js_modules, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
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       "    if (js_urls.length === 0 && js_modules.length === 0) {\n",
       "      run_callbacks();\n",
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       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
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       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
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       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
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       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'vtk': 'https://cdn.jsdelivr.net/npm/vtk.js@20.0.1/vtk', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'vtk': {'exports': 'vtk'}, 'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"vtk\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"gridstack\"], function(GridStack) {\n",
       "\twindow.GridStack = GridStack\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"notyf\"], function() {\n",
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       "      root._bokeh_is_loading = css_urls.length + 3;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n",
       "    }    if (((window['vtk'] !== undefined) && (!(window['vtk'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/abstractvtkplot/vtk.js@20.0.1/vtk.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) >= 0) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) >= 0) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/bundled/abstractvtkplot/vtk.js@20.0.1/vtk.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\"];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n",
       "    },    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, js_modules, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
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i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'vtk': 'https://cdn.jsdelivr.net/npm/vtk.js@20.0.1/vtk', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'vtk': {'exports': 'vtk'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"vtk\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 3;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n    }    if (((window['vtk'] !== undefined) && (!(window['vtk'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/abstractvtkplot/vtk.js@20.0.1/vtk.js'];\n      for (var i = 0; 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i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/bundled/abstractvtkplot/vtk.js@20.0.1/vtk.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n  var js_modules = [];\n  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\"];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n    },    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, js_modules, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
       "}\n",
       "\n",
       "\n",
       "    function JupyterCommManager() {\n",
       "    }\n",
       "\n",
       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
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Application\",\"version\":\"2.4.3\"}};\n",
       "    var render_items = [{\"docid\":\"9c393fd9-10be-4efc-a036-98ae3765c83d\",\"root_ids\":[\"1003\"],\"roots\":{\"1003\":\"18a73d62-22b9-4737-baa5-5176c085d6db\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['vtk'] !== undefined) && ( root['vtk'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
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       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
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       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "VTKRenderWindowSynchronized(vtkXOpenGLRenderWindow, orientation_widget=True, sizing_mode='stretch_width')"
      ]
     },
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1003"
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/aistudio\r\n"
     ]
    }
   ],
   "source": [
    "import pyvista as pv\n",
    "pv.set_jupyter_backend('panel')\n",
    "pv.start_xvfb()\n",
    "mesh_pv = pv.read('room_tet_remesh.vtk')\n",
    "mesh_pv.plot(show_edges=True, color=True)\n",
    "\n",
    "%cd /home/aistudio/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**对3D散点进行四面体化得到的网格：**\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/6b25969b6ce04e279b7d2e9645c3b3b374c6160414e94cd69ec4b2991aea7dd5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. 基于Paddle训练神经网络模型\n",
    "\n",
    "接下来，我们使用百度飞桨开发的机器学习库PaddlePaddle为后端的DeepXDE来搭建PINNs神经网络模型，并且使用来自Fluent得到的流场结果（速度$u$、$v$和$w$，压力$p$）进行纯数据驱动的监督学习，则PINNs退化为FCNNs，但在预测阶段我们可以使用PINNs来预测每个位置的PDEs残差。DeepXDE提供了建立神经网络结构，设置边界条件等功能，并可以使用Adam和L-BFGS等经典优化器来进行训练。\n",
    "\n",
    "对于室内空气流动问题，我们选择**三维稳态Navier-Stokes方程**作为控制方程。描述不可压缩流动的质量和动量守恒的三维稳态NS方程可以写成以下形式：\n",
    "\n",
    "$$\n",
    "\\frac{\\partial u}{\\partial x}+\\frac{\\partial v}{\\partial y}+\\frac{\\partial w}{\\partial z}=0, \\\\\n",
    "u \\frac{\\partial u}{\\partial x}+v \\frac{\\partial u}{\\partial y}+w \\frac{\\partial u}{\\partial z}=-\\frac{1}{\\rho} \\frac{\\partial p}{\\partial x}+\\nu\\left(\\frac{\\partial^2 u}{\\partial x^2}+\\frac{\\partial^2 u}{\\partial y^2}+\\frac{\\partial^2 u}{\\partial z^2}\\right), \\\\\n",
    "u \\frac{\\partial v}{\\partial x}+v \\frac{\\partial v}{\\partial y}+w \\frac{\\partial v}{\\partial z}=-\\frac{1}{\\rho} \\frac{\\partial p}{\\partial y}+\\nu\\left(\\frac{\\partial^2 v}{\\partial x^2}+\\frac{\\partial^2 v}{\\partial y^2}+\\frac{\\partial^2 v}{\\partial z^2}\\right), \\\\\n",
    "u \\frac{\\partial w}{\\partial x}+v \\frac{\\partial w}{\\partial y}+w \\frac{\\partial w}{\\partial z}=-\\frac{1}{\\rho} \\frac{\\partial p}{\\partial z}+\\nu\\left(\\frac{\\partial^2 w}{\\partial x^2}+\\frac{\\partial^2 w}{\\partial y^2}+\\frac{\\partial^2 w}{\\partial z^2}\\right),\n",
    "$$\n",
    "\n",
    "其中，$u$, $v$和 $w$对应$x,y,z$方向的速度分量，$p$ 为压力。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "该案例使用FCNN以纯数据驱动的方式来拟合流场，此处我们直接利用Fluent得到的流场数据（速度、密度、压力）作为监督数据，搭建神经网络进行训练。使用Adam和L-BFGS优化器共同训练模型，并采用学习率逐步递减的分段训练策略。模型的训练可以运行各个网格优化level的2_PINN_training文件内的python脚本来完成："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 纯数据驱动训练模型（约10分钟）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true,
    "execution": {
     "iopub.execute_input": "2023-11-29T02:45:34.197210Z",
     "iopub.status.busy": "2023-11-29T02:45:34.196381Z",
     "iopub.status.idle": "2023-11-29T02:57:27.370337Z",
     "shell.execute_reply": "2023-11-29T02:57:27.369467Z",
     "shell.execute_reply.started": "2023-11-29T02:45:34.197180Z"
    },
    "jupyter": {
     "outputs_hidden": true
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/aistudio/work/room/level1/2_PINN_training\r\n",
      "Using backend: paddle\r\n",
      "Other available backends: tensorflow.compat.v1, tensorflow, pytorch, jax.\r\n",
      "paddle supports more examples now and is recommended.\r\n",
      " \r\n",
      "Set the default float type to float32\r\n",
      "Figure(1920x1440)\r\n",
      "(1479, 7)\r\n",
      "W1129 10:45:37.631912  5323 gpu_resources.cc:85] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 12.0, Runtime API Version: 11.2\r\n",
      "W1129 10:45:37.635644  5323 gpu_resources.cc:115] device: 0, cuDNN Version: 8.2.\r\n",
      "Compiling model...\r\n",
      "'compile' took 0.000376 s\r\n",
      "\r\n",
      "Warning: epochs is deprecated and will be removed in a future version. Use iterations instead.\r\n",
      "Training model...\r\n",
      "\r\n",
      "Step      Train loss    Test loss     Test metric\r\n",
      "0         [1.18e+02]    [1.18e+02]    []  \r\n",
      "1000      [1.52e+00]    [1.52e+00]    []  \r\n",
      "2000      [2.06e-01]    [2.06e-01]    []  \r\n",
      "3000      [8.63e-02]    [8.63e-02]    []  \r\n",
      "4000      [3.94e-02]    [3.94e-02]    []  \r\n",
      "5000      [1.94e-02]    [1.94e-02]    []  \r\n",
      "6000      [1.23e-02]    [1.23e-02]    []  \r\n",
      "7000      [9.06e-03]    [9.06e-03]    []  \r\n",
      "8000      [6.60e-03]    [6.60e-03]    []  \r\n",
      "9000      [5.11e-03]    [5.11e-03]    []  \r\n",
      "10000     [4.08e-03]    [4.08e-03]    []  \r\n",
      "11000     [3.39e-03]    [3.39e-03]    []  \r\n",
      "12000     [2.90e-03]    [2.90e-03]    []  \r\n",
      "13000     [2.57e-03]    [2.57e-03]    []  \r\n",
      "14000     [2.12e-03]    [2.12e-03]    []  \r\n",
      "15000     [2.84e-03]    [2.84e-03]    []  \r\n",
      "16000     [1.74e-03]    [1.74e-03]    []  \r\n",
      "17000     [1.47e-03]    [1.47e-03]    []  \r\n",
      "18000     [1.42e-03]    [1.42e-03]    []  \r\n",
      "19000     [1.23e-03]    [1.23e-03]    []  \r\n",
      "20000     [1.10e-03]    [1.10e-03]    []  \r\n",
      "\r\n",
      "Best model at step 20000:\r\n",
      "  train loss: 1.10e-03\r\n",
      "  test loss: 1.10e-03\r\n",
      "  test metric: []\r\n",
      "\r\n",
      "'train' took 91.827021 s\r\n",
      "\r\n",
      "Saving loss history to ./Train_history/loss.dat ...\r\n",
      "Saving training data to ./Train_history/train.dat ...\r\n",
      "Saving test data to ./Train_history/test.dat ...\r\n",
      "Figure(640x480)\r\n",
      "Warning: 20000 points required, but 20164 points sampled.\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Compiling model...\r\n",
      "'compile' took 0.000346 s\r\n",
      "\r\n",
      "Warning: epochs is deprecated and will be removed in a future version. Use iterations instead.\r\n",
      "Training model...\r\n",
      "\r\n",
      "Step      Train loss    Test loss     Test metric\r\n",
      "20000     [1.10e-03]    [1.10e-03]    []  \r\n",
      "21000     [1.04e-03]    [1.04e-03]    []  \r\n",
      "22000     [9.42e-04]    [9.42e-04]    []  \r\n",
      "23000     [8.53e-04]    [8.53e-04]    []  \r\n",
      "24000     [8.05e-04]    [8.05e-04]    []  \r\n",
      "25000     [7.21e-04]    [7.21e-04]    []  \r\n",
      "26000     [6.73e-04]    [6.73e-04]    []  \r\n",
      "27000     [6.41e-04]    [6.41e-04]    []  \r\n",
      "28000     [5.97e-04]    [5.97e-04]    []  \r\n",
      "29000     [5.71e-04]    [5.71e-04]    []  \r\n",
      "30000     [5.45e-04]    [5.45e-04]    []  \r\n",
      "31000     [5.20e-04]    [5.20e-04]    []  \r\n",
      "32000     [5.07e-04]    [5.07e-04]    []  \r\n",
      "33000     [6.26e-04]    [6.26e-04]    []  \r\n",
      "34000     [4.73e-04]    [4.73e-04]    []  \r\n",
      "35000     [4.56e-04]    [4.56e-04]    []  \r\n",
      "36000     [6.32e-04]    [6.32e-04]    []  \r\n",
      "37000     [4.25e-04]    [4.25e-04]    []  \r\n",
      "38000     [4.53e-04]    [4.53e-04]    []  \r\n",
      "39000     [5.10e-04]    [5.10e-04]    []  \r\n",
      "40000     [4.02e-04]    [4.02e-04]    []  \r\n",
      "\r\n",
      "Best model at step 40000:\r\n",
      "  train loss: 4.02e-04\r\n",
      "  test loss: 4.02e-04\r\n",
      "  test metric: []\r\n",
      "\r\n",
      "'train' took 90.009436 s\r\n",
      "\r\n",
      "Saving loss history to ./Train_history/loss.dat ...\r\n",
      "Saving training data to ./Train_history/train.dat ...\r\n",
      "Saving test data to ./Train_history/test.dat ...\r\n",
      "Figure(640x480)\r\n",
      "Warning: 20000 points required, but 20164 points sampled.\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Compiling model...\r\n",
      "'compile' took 0.000273 s\r\n",
      "\r\n",
      "Warning: epochs is deprecated and will be removed in a future version. Use iterations instead.\r\n",
      "Training model...\r\n",
      "\r\n",
      "Step      Train loss    Test loss     Test metric\r\n",
      "40000     [4.02e-04]    [4.02e-04]    []  \r\n",
      "41000     [3.77e-04]    [3.77e-04]    []  \r\n",
      "42000     [3.63e-04]    [3.63e-04]    []  \r\n",
      "43000     [3.46e-04]    [3.46e-04]    []  \r\n",
      "44000     [3.32e-04]    [3.32e-04]    []  \r\n",
      "45000     [3.31e-04]    [3.31e-04]    []  \r\n",
      "46000     [3.19e-04]    [3.19e-04]    []  \r\n",
      "47000     [2.94e-04]    [2.94e-04]    []  \r\n",
      "48000     [2.83e-04]    [2.83e-04]    []  \r\n",
      "49000     [2.73e-04]    [2.73e-04]    []  \r\n",
      "50000     [2.61e-04]    [2.61e-04]    []  \r\n",
      "51000     [2.53e-04]    [2.53e-04]    []  \r\n",
      "52000     [2.42e-04]    [2.42e-04]    []  \r\n",
      "53000     [2.32e-04]    [2.32e-04]    []  \r\n",
      "54000     [2.31e-04]    [2.31e-04]    []  \r\n",
      "55000     [2.18e-04]    [2.18e-04]    []  \r\n",
      "56000     [2.09e-04]    [2.09e-04]    []  \r\n",
      "57000     [2.03e-04]    [2.03e-04]    []  \r\n",
      "58000     [1.97e-04]    [1.97e-04]    []  \r\n",
      "59000     [1.92e-04]    [1.92e-04]    []  \r\n",
      "60000     [2.63e-04]    [2.63e-04]    []  \r\n",
      "\r\n",
      "Best model at step 59000:\r\n",
      "  train loss: 1.92e-04\r\n",
      "  test loss: 1.92e-04\r\n",
      "  test metric: []\r\n",
      "\r\n",
      "'train' took 88.247504 s\r\n",
      "\r\n",
      "Saving loss history to ./Train_history/loss.dat ...\r\n",
      "Saving training data to ./Train_history/train.dat ...\r\n",
      "Saving test data to ./Train_history/test.dat ...\r\n",
      "Figure(640x480)\r\n",
      "Warning: 20000 points required, but 20164 points sampled.\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Compiling model...\r\n",
      "'compile' took 0.000385 s\r\n",
      "\r\n",
      "Training model...\r\n",
      "\r\n",
      "Step      Train loss    Test loss     Test metric\r\n",
      "60000     [2.63e-04]    [2.63e-04]    []  \r\n",
      "61000     [1.24e-04]    [1.24e-04]    []  \r\n",
      "62000     [9.47e-05]    [9.47e-05]    []  \r\n",
      "63000     [7.66e-05]    [7.66e-05]    []  \r\n",
      "64000     [6.50e-05]    [6.50e-05]    []  \r\n",
      "65000     [5.59e-05]    [5.59e-05]    []  \r\n",
      "66000     [4.86e-05]    [4.86e-05]    []  \r\n",
      "67000     [4.23e-05]    [4.23e-05]    []  \r\n",
      "68000     [3.78e-05]    [3.78e-05]    []  \r\n",
      "69000     [3.57e-05]    [3.57e-05]    []  \r\n",
      "70000     [3.56e-05]    [3.56e-05]    []  \r\n",
      "71000     [3.56e-05]    [3.56e-05]    []  \r\n",
      "72000     [3.56e-05]    [3.56e-05]    []  \r\n",
      "73000     [3.56e-05]    [3.56e-05]    []  \r\n",
      "74000     [3.55e-05]    [3.55e-05]    []  \r\n",
      "75000     [3.55e-05]    [3.55e-05]    []  \r\n",
      "\r\n",
      "Best model at step 75000:\r\n",
      "  train loss: 3.55e-05\r\n",
      "  test loss: 3.55e-05\r\n",
      "  test metric: []\r\n",
      "\r\n",
      "'train' took 405.961893 s\r\n",
      "\r\n",
      "Saving loss history to ./Train_history/loss.dat ...\r\n",
      "Saving training data to ./Train_history/train.dat ...\r\n",
      "Saving test data to ./Train_history/test.dat ...\r\n",
      "Figure(640x480)\r\n",
      "Warning: 20000 points required, but 20164 points sampled.\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "Figure(1200x900)\r\n",
      "/home/aistudio\r\n"
     ]
    }
   ],
   "source": [
    "# 室内空气流动，Level1网格训练\n",
    "%cd /home/aistudio/work/room/level1/2_PINN_training/\n",
    "!python level1_training_room.py\n",
    "%cd /home/aistudio/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 直接加载训练好的模型，并绘制预测流场\n",
    "\n",
    "以**原网格Level1**为例，最终训练完成的模型预测的流场**速度**和**压力**云图如下，云图相对光滑，但与Fluent结果点对点差距很小："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:13:45.870701Z",
     "iopub.status.busy": "2023-11-29T08:13:45.870106Z",
     "iopub.status.idle": "2023-11-29T08:14:02.628040Z",
     "shell.execute_reply": "2023-11-29T08:14:02.626738Z",
     "shell.execute_reply.started": "2023-11-29T08:13:45.870663Z"
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "加载哪个level?（输入数字如1，2...） 1\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiling model...\r\n",
      "'compile' took 0.000431 s\r\n",
      "\r\n",
      "Warning: 20000 points required, but 20164 points sampled.\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 加载室内空气流动level1模型并展示流场\n",
    "from work.restore_model_tools import restore_model, plot_room_flow_field\n",
    "level1_room_model = restore_model(model_path='/home/aistudio/work/room/level1/2_PINN_training/Model/model-75000.pdparams')\n",
    "plot_room_flow_field(level1_room_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6. 基于Edges中点的三维网格自适应细化算法\n",
    "\n",
    "\n",
    "网格逐级细化过程大体思路是，\n",
    "\n",
    "- 原网格先使用Fluent进行模拟，FCNNs训练模型，但使用PINNs来预测模型。\n",
    "- 在流场区域内布满**每个单元（cell）的质心点来计算PDEs的残差值大小**，来得到一组残差较大的单元质心点集，对应其质心点的每个四面体单元都需要进行细化。\n",
    "- 之后将**需要被细化的每个四面体单元的所有Edges中点**都加入到原有的网格点集中，即可生成加密后的网格。\n",
    "- 再使用Fluent进行模拟，继而利用CFD数据训练模型，循环执行2、3步骤即可逐级对网格进行加密。\n",
    "\n",
    "\n",
    "我们依然采用原网格边（Edge）的中点作为预测训练好的模型PDEs残差的点，然后再进行Delaunay四面体化去生成加密后的网格，可以得到较好的网格质量和细化效果。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 基于Edges中点的四面体网格细化\n",
    "\n",
    "为此我们提出并采用**基于四面体网格边（Edge）中点的一变八（1to8）细分网格**的算法。示意图如下：\n",
    "\n",
    "主要思路为：\n",
    "- 对每一个tetrahedron element的每条边（Edge）取中点形成新的顶点。\n",
    "- 新顶点与原四面体的四个顶点形成4个新的细分四面体，这4个四面体与原四面体相似。\n",
    "- 剩余的一个八面体则被等拆分为4个四面体。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/ee15e6acdab8403fb9b4dea3814d87f15d6616657f27469dab11c35525c764c5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**接下来的网格细化过程展示以Fluent生成的初始Level1网格为例对代码和流程进行详细说明。**\n",
    "\n",
    "网格细化的整体代码均在各level/3_PINN_refine_mesh文件夹的PINNs_guide_mesh_refinement.py中，为了解具体过程，在此处运行每块并作详细说明："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先得到原网格的节点和四面体单元的信息："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:14:02.630929Z",
     "iopub.status.busy": "2023-11-29T08:14:02.630195Z",
     "iopub.status.idle": "2023-11-29T08:14:02.718325Z",
     "shell.execute_reply": "2023-11-29T08:14:02.717105Z",
     "shell.execute_reply.started": "2023-11-29T08:14:02.630891Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "原网格节点个数: 1479\r\n",
      "原网格四面体个数: 7010\r\n"
     ]
    }
   ],
   "source": [
    "level = 1\n",
    "# Get the node coordinates\n",
    "mesh = meshio.read('work/room/level'+str(level)+'/0_Mesh_files/room_tet_remesh.vtk', file_format='vtk')\n",
    "points = mesh.points\n",
    "\n",
    "# Delaunay四面体化\n",
    "# points 输入散点；furthest_site 为True时，计算最远点；incremental 为True时，允许增量添加点；qhull_options 为qhull参数，具体可参考qhull\n",
    "tri = Delaunay(points, furthest_site=False, incremental=False, qhull_options=None)\n",
    "# 加密前：获取三角形网格的顶点和三角形索引\n",
    "vertices = tri.points\n",
    "tetrahedrons = tri.simplices\n",
    "print(\"原网格节点个数:\", vertices.shape[0])\n",
    "print(\"原网格四面体个数:\", tetrahedrons.shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算每个四面体的质心"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:14:02.720345Z",
     "iopub.status.busy": "2023-11-29T08:14:02.719765Z",
     "iopub.status.idle": "2023-11-29T08:14:02.765756Z",
     "shell.execute_reply": "2023-11-29T08:14:02.764362Z",
     "shell.execute_reply.started": "2023-11-29T08:14:02.720310Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from work.mesh_refinement_tools import tetrahedron_centroid\n",
    "centroid_points = tetrahedron_centroid(tetrahedrons, vertices)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "加载模型并找到PDEs残差最大的质心点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:14:02.768104Z",
     "iopub.status.busy": "2023-11-29T08:14:02.767216Z",
     "iopub.status.idle": "2023-11-29T08:14:03.994580Z",
     "shell.execute_reply": "2023-11-29T08:14:03.993260Z",
     "shell.execute_reply.started": "2023-11-29T08:14:02.768068Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiling model...\r\n",
      "'compile' took 0.000756 s\r\n",
      "\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from work.restore_model_tools import restore_model, standardize_NS_Equations_3D, data\n",
    "from work.mesh_refinement_tools import get_top_k_indices, plot_room_add_points_3d\n",
    "level1_room_model = restore_model(model_path = \"work/room/level\"+str(level)+\"/2_PINN_training/Model/model-75000.pdparams\")\n",
    "X = centroid_points\n",
    "standardize_X = data.transform_inputs(X)\n",
    "[f1, f2, f3, f4] = level1_room_model.predict(standardize_X, operator=standardize_NS_Equations_3D)\n",
    "err_eq = np.absolute(f1) + np.absolute(f2) + np.absolute(f3) + np.absolute(f4)\n",
    "x_id = get_top_k_indices(err_eq, k=1000)\n",
    "add_points = X[x_id]\n",
    "plot_room_add_points_3d(add_points)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算需要被细化的四面体单元的Edge中点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:14:03.997491Z",
     "iopub.status.busy": "2023-11-29T08:14:03.996978Z",
     "iopub.status.idle": "2023-11-29T08:14:04.283082Z",
     "shell.execute_reply": "2023-11-29T08:14:04.281549Z",
     "shell.execute_reply.started": "2023-11-29T08:14:03.997442Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "待加密四面体网格个数: (1000, 4)\r\n",
      "待加密四面体边中点个数: (1763, 3)\r\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from work.mesh_refinement_tools import tetrahedron_midpoint, remove_duplicate_points\n",
    "tets_id = x_id\n",
    "refine_tets = tetrahedrons[tets_id]\n",
    "refine_midpoints = tetrahedron_midpoint(refine_tets, vertices)\n",
    "refine_midpoints = remove_duplicate_points(refine_midpoints)\n",
    "print(\"待加密四面体网格个数:\", refine_tets.shape)\n",
    "print(\"待加密四面体边中点个数:\", refine_midpoints.shape)\n",
    "plot_room_add_points_3d(refine_midpoints)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对加密后的新的网格节点进行Delaunay四面体化可生成加密网格，并输出为VTK文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:14:04.286790Z",
     "iopub.status.busy": "2023-11-29T08:14:04.285300Z",
     "iopub.status.idle": "2023-11-29T08:14:04.779311Z",
     "shell.execute_reply": "2023-11-29T08:14:04.778155Z",
     "shell.execute_reply.started": "2023-11-29T08:14:04.286736Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# points 输入散点；furthest_site 为True时，计算最远点；incremental 为True时，允许增量添加点；qhull_options 为qhull参数，具体可参考qhull\n",
    "refined_tet = Delaunay(np.vstack((vertices, refine_midpoints)), furthest_site=False, incremental=False, qhull_options=None)\n",
    "refined_mesh_info = MeshInfo()\n",
    "refined_mesh_info.set_points(refined_tet.points)\n",
    "refined_mesh_info.set_facets(refined_tet.convex_hull)\n",
    "refined_mesh = build(refined_mesh_info, options=Options(\"p\"))\n",
    "new_mesh = \"work/room/level\"+str(level)+\"/3_PINN_refine_mesh/level\" + str(level + 1) + \"_refined_room.vtk\"\n",
    "refined_mesh.write_vtk(new_mesh)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**运行以下代码进行加密网格的可视化交互(可鼠标拖动查看网格)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-11-29T08:14:04.781068Z",
     "iopub.status.busy": "2023-11-29T08:14:04.780753Z",
     "iopub.status.idle": "2023-11-29T08:14:08.922178Z",
     "shell.execute_reply": "2023-11-29T08:14:08.920826Z",
     "shell.execute_reply.started": "2023-11-29T08:14:04.781040Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
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       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
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       "\n",
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       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, js_modules, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
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       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'vtk': 'https://cdn.jsdelivr.net/npm/vtk.js@20.0.1/vtk', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'vtk': {'exports': 'vtk'}, 'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"vtk\"], function() {\n",
       "\ton_load()\n",
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       "      require([\"gridstack\"], function(GridStack) {\n",
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       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/abstractvtkplot/vtk.js@20.0.1/vtk.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
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       "      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) >= 0) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) >= 0) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
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       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/bundled/abstractvtkplot/vtk.js@20.0.1/vtk.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\"];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n",
       "    },    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, js_modules, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
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i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/bundled/abstractvtkplot/vtk.js@20.0.1/vtk.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n  var js_modules = [];\n  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\"];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n    },    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, js_modules, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "\n",
       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
       "}\n",
       "\n",
       "\n",
       "    function JupyterCommManager() {\n",
       "    }\n",
       "\n",
       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
       "        comm_manager.register_target(comm_id, function(comm) {\n",
       "          comm.on_msg(msg_handler);\n",
       "        });\n",
       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
       "          comm.onMsg = msg_handler;\n",
       "        });\n",
       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
       "          function processIteratorResult(result) {\n",
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       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
       "      if (comm_id in window.PyViz.comms) {\n",
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       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
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FTi3qaYNp6knEXpQm+3OzRIX16VLL+8AlFPSy4ayW3t4PkK42vKOp5gom7QtxR5Z9g3KWSy++ouKstHvkqY+SpxlOt/dh5w/Q51LirwoKvKXJ/dlLaB42RrxFj977p072Subv5V2f1T1/F05ebWH/CGymsVFt7WXu7qP+6G3dXmlK69zH9uypvHzG+0s/8pZvq7ifurvJD3+7SNcqnrI2tvB6K21hMvf3T5wjjPgoLPsLs3VN1DzQeaPbpJXmA8QCrD1udmT5DjYea/eBTlaZUWzez9vZW2s3E6Lqp6dtHdW0qRpfBpk9f6TtYTNpBln5jpR0k7qe6Njfe3NpPvUeZ/fqrrCHGQ5SmVNmDrfyBKi/0oW0jrH2byD4jxJQ9zMrfVGUNEw9SWcONh1s8cSMtfrDqHyneTHVtabyltX+IytrCGPlE4xOtveg+LX22Mt7K2jNUfT1NvLnqC32oa5TVN0y6jxIPV9qJxhMtnnomWXtGqP5JYsrdNX1ONx6lsODTrX3UNdnqG6myJ4uRd/8XT1JYqbJ3s/JHqazdxOi2h+kHn6aw4GkKg7dOn33S5ybj/RQWfEX6jDYerTTBDylN8E0KK5V2f0s/WmnHGI9RmlLyg+lztfG+/4rfRmHBVyss+AqVUSp8hqXfRulniLet1N+X4v0AviXJ1xkjX2vM8/AW44vteQtfa+9z21Xq775HGh9p72cw77JnG19r9W+n+q83Rj7H+HzTb6zirzNGvtWY7wvnGhN3g/G5Vh9MXHzf2F58m/GZlh/m+8WZxrcn+UZj8t5uTFx8XxmH/xT5+xKMfLLxNCsPvquo5wkm7g5j8k4zJu4u8XjVd7fxaVY/PLPI78/jpc9NxuSdaUzam42R4/vkDunzSJG/f8L3JvkBY96t7zU+3cqDSfuIMWWdbkzaeD/fUfa+1XiGvS/tqP6/xRh5hjFp7zS+0/p/QqX+/nWFMfI9xqS/2vge658J8o87je8w/9hJ9r3L+D7rr53U//cYI19pjHyJMfJ94p3Vv868+91vzPv8ZcbTrb9h0k43pqz4frCL4i8zRr7G+KEkzzK+yOqHSfuQ8Szzj13kP/H9jWcBz454HvAcYO7fyxg5nie7Ku2exsjnGyPH822y8u5tPMXqm6y4KeLdJEf5u6v+yI9u+5h+8MWV/PyBT1NYqXIuMv32VPn7Gu+rNKXKpaz9jPez+sm7v+Wforh43uyt9MH7SJd4XpJvhtV3QPr8J/XFnCLzHBvf8APW3weoP2cbP1rUywgm7lHxgekztfL/+QSFBc82fzlQaWcbE/eg8aEqI5i4eF8/qFL/bTR+HztI7TvO4k+u5N9P4eMUFvyI2eMg2eM/xg/bfMbv6GdX8u/78OEKg/kd96xK/v37ENV9lhi9eZc+w/gMa99h0i3SH66yzjE+x+qjLN5FLzC+wMrn3zX4t4krjZHj30vIe5nlh09UGMy/U1ySPtONj1dY8PRK/vePY8RR37Fqy6XGl1p76Iu5ybaPFZnPs/6BiTvPmL6Zq/THyxahz1SVF/43Vba90OIvrOT6pkqO8k6Q7SI9tmBuuc74OrMPvw3xb1k3GiPfYowcvx/Rrsutf09Wey8XnyLb3Wx8cyX/e9mpKu92Y+T4PslcxPvzfcbIMT/RlnusPfD5CivVdnzhKuOrzB7Uc0clf585U/XfIaZd11t/n6W2XS+eprSh39nyhRuMka81vtb69xyVHemxyyyz/7my1yzxeerfC42RrzG+xuyPLf5j9oAvUlgp29xm9oEvU1ipsm+18i9U2lvF09WWu4zvquTxQl3/tfrgGQor1Y8vVPL8frFs+YL4EtlrpvFMqw/b3W32u1R9c7eYttxr7YGvU1gpO91p/Xm52nqnGF2fNX3hqxUG893no0r+/gM/pLBSdkDXOcZzKnk8YMuHzZ5XSdeHxdS10Oq7WnUtFF+jvLONZ5v+18o29xvfb/bEFvjGU8ZPmX2uV1kPGD9g9r1B8iPGj1h9+PGTlTx/wLMUVqrf6etvjb+t5O+z2On5Svb/m2W/58WU+2Ilzx+3qOwXxbfKlmGf29S2R40fNXvfrrxPGyPHfMDf1yp5vN+h+NfEd6qux4wfM/vhC3PT5yXjlyrZP+5S38wV3628Txg/YfaeKVs/bvy45advGXvvGb9n/X2v5FeMXzH73Ke2/WD8QyWPT+p+xuq/X7o9I6bfFlh/z1LfLRA/IPs8Z/yctRdfX6aa/R3+SGEwfrJZNY83+FuFlerXl63/H1bb3jJ+S2lK6U7d84znWXsoZ77172zlnS+mH9+vZP+co/59X0xfMJf8bvy79c+jsn/oRz++Wsn+Mle2flX8mOp+w/gNsydp37T0j6stb4qfUNrXjV+39tNv31fyeHpSffe9+Cnp/rnx55XsT7R19WpuL/yswuCnVfY3lczIMZ6ekS5vG79t+lPWQivvObX/nUrmd6x9z6sv/mf8v0r2R/wa/x5QzYwc8xO6vGv6zFPZ74pflG0aVzMjR/vox5/NH15S33xh/IXSwPjWh5XsX/BXCgt+S2Gl7I79FxkvqmR/mq+8Hxh/UMn+86ps+5nxZ6Yf/bJGNc8Hr6m/1lB7X5e9P65k/tjsQz2fWP+8ofo/Eb8p235q/KnpQztYJPWV8SKFlcr7peV/W3V/KX5HdX1t/LXp+67k74y/s/z4Cf6yajUzcowHxsLWidtUM/+usGDiYrzgB2tVsz++r75fS+k/UH/9VMmM/KPxj2Y/0v5t6eGvFAYzT75TzfMnzFz5jpi2L7b2fyz7LBZTzy9mv09U/y9ixiJlP17NjBzj81PZ8vEi86/p81sl82/W358q7a/izxRfrWZGDv/8XPZdoZoZOcYD6RpU8/j6QvkbKD26PVFk/b6ULZ4QY0t8rWk1M3LY92vZ4k9j5P8WmZHDnoydTap5/MDMF5uImXeYf940Ro7nG7o9mcr7o5L5D9P3O/Xdk2L8dPtqnp9g/Hd7MeP62mqe/2B0u1a8SPbc2Bg5xt8/flnN/gAX1XpY8E8RJt2eLrJ+8LNFPSwYez0rJm+zas7/k3y7mfhn9W9HY+QYT+i1RDX3zy/SdwnF42cvFdkf4acSP1dkxjeeMibuJTH5Glazf8JNqvWwYNI2ETM33FfN8wPMWLlPTF/OS+mfLzJjq2eMnzd9YOLmGRMX/sA8M7ma5y8Y20wWY5dGSX6hyPx6UQ8LxlavWzxpw7//Sp8Xk/yKMX35ovGT1r9/Sd8njcn7svHL1t6/Nd7WrmZGjv7HDzvb+KzIVzuLq+qLVsbIKxqvaPNBobKXNV7W/LkUL2e8nPlTLf19zdoP48svGL9o/g3PT/JbxsivGZN3vph6Wlh/LKH6W6j+BmpPd+PuNj6WTH9fTXnfLjLjT68aP2f+B5P2feM3bHzAxL0hXirxu1YePM/6dynVP8/4vaKeJ/jNoh4WTN43xfTlatafcBOFlfLl+WbvRrJVC4tH/tDi3zH7NlLcO2Lmzatsfm6sufMqMXV/lNJ+XmRGXs3iXzL7NJH9PhIvnfjjJH9g/Ir1P7ygqKcJ/sDssbTs9YoxeReIeTbzrI/nM+NkmI2nphorw8T4fifz/2ZK29+4v9LAzWW/T4rMyF8aIy80XmD+Di80fZvL/8P+6NHextuyqru9eDnJ7YyRvy0yf2v9z9+vitz/LRT/lXh5+e+nxm+bf8Kf2fiBvy7qYcHk/d4Y+Wsxz1LeV46qZkaO5+uK8u2exj1tPK+U/i5OZS0qMi8yfeEvinqa4PfMv1aSfu8ZE/eFeOXEPyX5G2Ns9Z0x8k/Gn5g94W/MH1ZJ/Kv5O/xjkn83Rv7V+H2z5yoaX+8bE/ejuGXiX0z/lhpPC42/sPHTUv72gzHyz8bIv4h5bt5Sze9L8GSFwYzzZZOwkTHjn7DgjWy+Wl1j8Vdj5Hj+r6G55kVj5Hgfo5yR5h+tVP5I8ZpqT4y/NTX+vjH+zdq/pvrrf8bVsp4mmLiq2tNa4+ePInORhD+NiSss/Xc2vuA/zZ8YCw/beIC3VhjMu8od1fy+AvMsO874OKWBmauYyyYYT7D5qy1/y+w/8JJlPSyYsfqXxSMvafE/2nheJ/HfSW5YZm6ahEbGyH9Z+u9t/K6j8fu38V82f8CU3VTltdN817uaGXk5i8f+Mf/BS5S5v9op7RJKv27ixgjGCDEe1tV4+M0YuWbpkRuL19N4rBg3T8LSxottfMHLlPU0waT92+L/tvlsPem3jNKvr/kq/A9eKgnNLP5/Nl+tL/9byuIblNn/YfI2UDy2HmH2hjspDO6Q/jZJwupl5rZlHv8dNB/E/NZB88XnxsQ1sfSU1VaMrzP371fNvJ/5P7qMM306ydfHiXm2n1rNz3d4Y4XBG6j/YnxvoPHfwBh5BWPkVY2RWxgjh390qWquN6atMf/Dbcrc/i4an8sbI7c2Rm4j7qr+LoxXLHP/wq3Kelgwvr+acWHjASaulbhb4lWSsJbxSmUe793kr6sYNzR/h8m7kri75u5J1cyTrH97pL9rJqFlmXkZG19wS/P/HrL3GsaNrT9g4tYUb5h45SSsY4zczpi5rpFxO+uPDdUfSxqTdmUxbRtp7eul+TDa30v1NzVub/nh9cp6WDB51xPzrNukzM+7jTSeulg88iZixm23Ms+P8JYKCx6hMLiP/Dvmjz7yp/WNOydhbWPiOhs3M3+DSRvjp6/8qbnxBknoYEz/rmvcwfwLJm4D4+bmL4xtnqUPVTM/ZOO9n+b/aD/cNwmdjJFXM17N7NdPtusrZq452OYbeILCYH5X+l81/54FX6sweKDmj7DnQPnrqsYdzb8Hyp5djXuX9TTBxPUW8y7Fd7V4n9qU+dTsu6nK72OMvLHxmlY+TFx3Y8qK8TVI800n417mP4PkL62MN01Cf2PkXsaUtal4sPyhp/Fa5j8wcQOMkQca9yjzeBqs8baWMWl7iDdT361YZEaO34+HaP6I8QoPTcKGxu2tPHizsp4mmLjNjMkb89NQ8TDjdlY+TNwIY+SNjJFbGyPHfLe54kcat7H8MHFjjPuV+XkPI7cxJm0/Mc/dk6r5fXSYxuJJ4uHqrxjPwzUfdDcenIQhxkOs/4fLnweLR2gsTqlm3iV9trV45C0tforSwFto/MR8toX8d3Pjzuaf8KAyj0eYtFsaIw8Sj9T8vXM1M/Lhxsjx/NhS+g4vMyPH/DVK/THBeFyZnwfwlLIeFkzaKcakbWvc1vpvK7VvG+Pe1p6tNF/0NibtTsbI2xlvUeb5BiZuCzHffb6p5u8/8H0Kg0dr/on08Cjr/9Hyl42Nt0/CeGPkUcaUtb14DP2RhK2MB5j/jVF9OxoPsfJg4nY2pqyYj7ZJvHUSdjVmvtvamLixxmPN/7aRf8V8ua3K38UYeZIxc8tA44HWPnh0mecfmLyjxdtpfu5rjK6bGk82/eGJSdjfGHmyMWUNN0aeKB4rfXYzHmr6jNV8N9SYtHsaI+9gjBzzJ79j8NvFB9XMyPF7JnPHyTZ/wAcrDB4v/47xPV79s7fxltZ/8B5lHj8waQ80Rt5DvIP03c94hLUHPiwJexkzP48wJm6kMWUdJt5R421fY3x/O+PdyzweYNIeaoy8u5h5/Ypqft+ZoLn9CvFOGm+RfieVf7gx42W8MXEHGSPvY4wc44+588gknGOMHPPpzppvx1k88pFi5v0jzP/gM8p6WDBx2xpPURp4YpIPKPP4gw9OwlHGxO1sjP4HG5P2AOOdrb2T9Dy4spoZOb4v7ar5NfxnV/XXTsbHWH/vKn882hj5NGPkY8T87sRvSx9VM39Uzb//7ab5IvTfTfY4znhqEg4xJm6qMXG7GSPH/LV74nOTcILxiWU9LJj3jb2MSTvBmLgTjYmL95k9NB53NT4+CacbIx9rTNrJxsjHG5M25oM9GQ9JmGaMfIox7T/JeE+z154av3sakzfmh72Ym5JwpjHyqcanmr/tpfF0sjFxMd7w7aPNv+HzFRZ8ssLgvdPfC5JwZZn5fPOvvWWPC4wPNHvuLf870Jiyzhfvk/jiJJxtfGESrjDGVy80Ju5iY+aTQ41p++HGxB1jfLbZZ1/ND5caI19vjDzdGF/Y3xj5COPp5i+M4weq+fes/TS+HxDvn/5eloSzyszIxxnPKOtpgunv84yPMn+AiZthTFkxXx2Q+Loyz48HaDxdZXxbWU8TzLvkCcbknWJM3tvEBya+PAkXGU+19h2o9l1uzNiYakzeGC8HJb6mzOP7IM0Phxkjn2J8SRJuMibuEmPirhHzXONZdlk182XV/D5wSPp7rdn7EPnP1cZnmv8eIvufaXxDWS8jmLw3iA/VeLrFeFYSbjYmbpYxcRcaM5+fb0xczPeHyR/vNmasnm6MPN341jKPZ/iesh4WTFn3iHl23VTNzy/4FIUF87w+RXyE+ifmS/j+JMw0nmb+c4T84UbjmdafMHH3i4+UfS82vtP6C763rIcFk/YOY+R7xfzW9Gk1/94EP6ww+GjNFzGfHq258yKLv6/M88vRirtPfEySH7T2wbcn4SFjxsplxsi3G5P3cmPyPig+Vv57l/EM88djVd8MY9LOMUaebTzb6mdee6ua/33qOM1tb4mPx15mX/ixJDxpTNwVxleY/x8vf3/MmLwPi6cmfrTM8xf8fBJeNn6grIcF825xjTHyA8bkfdSYsuN95ATZ5wbjR5Iw1xjfesR4rtn/BM0H4X8nVuvPw1uNHy/zfHCixv+VxqT9j/EzZT1PMHHPiHlX5/eYOdXMc6r5/Z157s5qft6frPnvTjHj9sMyj2eYZ8MTZWbG93XGxH0opu63rf5TNZbeFp+m/on5Gn7J+gN+p6yHBf+3rIcFk3emMfJ/xacnnp+Et4x5nt9njDzfmPnteuOnyjx/wq+W9bBgyn5VfEbip63/z5B/3Gv8XBJeMUZ+2vhe8+8zNH6eE5+p+fgpY/r7HuMXzT/OlP6vGyO/KD5L4+d9Y+TPjHm2P2r8mfX/WerveP5PS/xsEt41/sD6Y5rm+weNSfuBMXHPGpM35vezEy+w+LNV30PGyLONkV8wRn7TGHmB+BzFzzF+2/Kfo/59wxj5bWPyzjWea/17rua/WcbIjxt/lIR5xsiPGb+WhE+MkT8ypqzXxOclXpiE94znWXr4PfOv8zS/zjMm7klj8i4UM2/MrObn3fmaO2aKL0h/vzB9LpD+zxg/Y/54gfz3Y2Pk742RvxBfmPibMs/vF2r+f8kY+Wtj5P8ZI38jni57fGX8QxI+NSbuB+NXzL7wp+Yf0+UfMd4vkm3uqmZG/tLikecbI8d8dXHi35Kw2Ji551tjxverxovNnhfLnq8bk/c38SWJFyXhJ2PGx9vGn5d5/Fyi9i4yJu/nxm+b/S5N/HsSvjNGftd4geW/VPPDAmPifjFG/l18mZ5tc6uZ59rz7PL0t1qrVP4sM9P+t4yxP2mC/zT7Xq75PvprhsbXR8Y/m//M0Hj50Zi4hcbE/W2M/LOYtrxs7YHnKAzmvfulav4+CT+nsOCbFAbzOyi/h/5mjBz/fni1xkc8X+GylsfP1ZrPvzNG/ssYuVEt8z+yMWXHfH9N4qYp7ldj5PeNGZu1WmbkpsakfdnSI8d45t9ilyryv8deq7YupX/vu072j/n0Os2nXxgj/2HMIcA/GhPXoJYZuSK+XuMp5ovrNZ/8bIy8hKUvank8wY1r9bBg0jYW36D+jfct+Ilqfl+Dl09p17f0pP3M0mPv5S2euF8tnrxPqLwb1d6Yj2/UfLzYeMmUvlktc8Nath9MXEOLJ++S4pukf/jrzfRVLY93eLlaPSyYuJ8sHrmw+GVq9TzBxC0j5nfOP6r53wvgjxQG3yp/jvkFXraW/R1eoVYPCybtUsbIK4hvk/8sbbxSkpsbE7eSMXFLGCPHfHGb5ovwt9sTN0nyKsbMX02Mmetj/oNJ28Li6YvfLJ646B++5/1Uzb8Xw28pDGaefaaan/93au56wfgFpYHv0nwc8ym8Wi3rCz+msOCZCgsmbczXd2u+WtH4n2e98VpJXtWY+STeB2DiahZPWWuJZ0r3qP+e9LdVimtZy9zA/Pse9WcD45bW//dofKxsjNxKfG/i1c1f75U/NzZubP4Dr5HktsbErWFM3Opi/u11pSL/+yv8q8Lg+5O8Xkq7Ti3zOmZfeM1aPU0wcY2MGRtrGjey8TJL7W1m3MbsMUvzRQvj1kluZ0xca2Pi2oh5Ln5Rzb9HwC8pDH5Q9l23lnkFmy/gjqY/TNqOxsuZPR+UPWK8813352r+vgt/qjCY35KwfYMiM3L8vvSI5ofwr0fkP2sbd0hye2PiOhi3t/5/RP4R88vsxD1r+fkA8yxoatypVk8TTNrljZvaeJqt8dNJzLvK59X8vjJHtvhc/J/09+lq7j94nsKCH1NYMPPVapYe+TGLb23z36Pypw2MO5v9YOK6GCN3Nl7bxuOjGu/hX8xt79n8NldtfU+MXq+Y/o9p/nhFzFr5tVN/r1lkRv7V4t9RGphn47vV/HyEe9fqYcH0T2/p96T8ta1xW/MXuE+Suxl3s/EAd01yL2PydjUmro/4qcR9rf/h7kne2Bi5r3Enm1+f0vy8jjFyd/F/pU8H4w7WX/BGph/co1YPCyZtD/HTmi9aGw9M8obGryoseJ7Cgjew+Qje0PyNvv7Q+vsZ+cqH4mdln5g/n9V829G4X5L7G3e0/npW/dXPuL/ZCz/5upq/Dzwn//la/LzatmktM/IAY9oz0HiA2e952beLcRez3wsaC9HeebLF+8bvmz15N+f7SNMiM3K8r78k3WP+Zqx9a+PtZc0t34qp60ur7xXp8qV4fvq7ifn3fLVvM2Pkoca9zJ/my98GGJN2E/GrqvuTauYhZk94y1o9LPgThcGvSb/NjftY+fCwJA8yHmT+8Jr8p48xZQ0Tvy5/6G3c08Yn/F01zy+vK21PiyftYGPk4cbI3yn/G4qP+QDewvLDI2r1sOCNzf/fkH8PMkYeIWYtJ9/11ikyI8f6Tt4DuFQm3lffki9VFM+ziWfzn9XMf1bz84q5uGOR52OYsjuK35W9YnwtSH9Hmj8tUN9uZYw80nhT84cF8r9NjYkL/8DvF9n4ek++v0j8vnz9e+PvzR/53rNskX8PgP9QGPyhylpczbzYxg/fA7Bl8yIzcnx/+ljjIdoHj07yNsbIo4xHmb9/LH8dakxZo8W0Y/skjzH+XmHBY8xeC+Vfw4y3Nv+Bt6vVw4K3rdXDgoeZvgul77Zi3tt4f2tSZEaO973P5O9R/mcaH1sYf1fN4+cz6TfWeKyNp8/ln78b/27z3z/zZJH9+4vwTfGX6s/wj6/UP+GfX8k/xxjvkORxxth6B+Nx1j9fyf7RH9RdFLn+r9XeQsy78MpFfh+G+S6ysph21Yrs39+qvTXFU9Yuqa6qMXJhjP12kT60++/02dF4scKCdzT9f0g8Ick7GSOPN6b9E4y3MXvB481ffpB/xXhYpLYsUWRGjvH3o/QPf/xR7R1rTPk7G29n+sE7W/sXq/xoL2N5+SKP5580Ny4v/ln+vIIxcsyXv6S/SyaeWMv8t8KCseffln6i2esX2XcHY+ToH96LeT/uUmRGju+rzGNtivz+8JvmsjZifGXpIvvL7xo/S4uZt1oXef77Q/NZazHPlg2K/HyBeTfZQPyn7BHl/ZW4YZIn1TJPsv75S+1f0tLjTxMtfmfzt79ky4ZKjx0bFTn/3+rPRmL6bjnrv4rG3nJixga+EPpVpWtDi0dubNzYxhN/m9l4LhTfTFxKjvpqss0yxsuYvy8hDv2ZB9ay+bSB5oK1xLS7hdljSeVtIV5KvtDduLv1V0OlXcV4FWtvI+nT0rilld9Y6Vc1XtXa30S6tjNuZ+MHW6xm9oDXUFjwCgqDl1Fc6NNUvh3ta6b6Vzde3eyPL3cwf4bXV1jw8gqDGQfdijx+llXebmLKXc/8aznVt564hXRtZdzK7L280kZ9tLWTtXcF2auTmHctxt5mxsibGiPH+xjzwoZFfn7APRUW3EVh8MqKC/9aRfq2NW5r/U3b1rX2tVT/rCsmXXvrj1WVv714NbW1s3Fny7+60oY915AtIn0rpe1q3NX0Za7kXXWw8eAiz5+t1fd9jPtY/7aR3Nu4t/kbdtqoyP69luy3kZi6B1n9a6tvBonbSt8exj3MPvQ1Y3WY8TDrf+rtZ/7RTnX3E68rW/Uy7mX2wq4bm//BfRUW3F5hMOn6F3m8rK+0/cXtpX+k76C4sG9H+We0v5N0HWA8wPq3szj0xxZbmj02UF9sKaZfhxTZn7vI9kPEtHug2buryt7EeBOlgen7Haz/u6ktO4i7K24b421Mnx4qK+yBbwxPn5HGPRUWPNL8p6d0j/hessdOxjuZ/hsp/2jj0eYPvaV76EtbdrH29FF/7SLuK/13NUaeZDzJ/GVj8UTjieYf6LG99Xc/6be9uL/SR/0DFBftHai2TjaebPptorQRj69tZv7G36FFHo+DFD9UPFhy+Atxm1v8ZvK9zcVDFBf9M1RxI4xHWDxxW1j85ipvC/Ew+U7wcKUNf0He6l88SmHBWygM3kLlbW28tcWPVN7wly3lG5GedGOs/FGKGyPeSvK2xttaeaTdLn3GGm+jsOCxVt5o5Q9/GKP4ccbjrD7K2sHK21bx443HW3mk29H02U75dxSPlTzBeILVv73KC38cp/ioj787W/x4xe8spq5drL4dxRONJ1r9E8STjCdZeTtJDn9H3vVfPKnI44N7SbkPM+7L5K5Q7teM+za5d5S7KOM+SO4G5X7LuM+SfIcW+T5M0nLXY9zvSNncJxn3R1I298fEfTDc7cldK3F/C+VOK/L9NJTN3Tdxnw3lcJ9O3J/D3ZXc9RP391AvdxfG/UDcZchdg3F/IX+5XyjuE+IevsuLfF8RzN1tcX8fd+1xv0ncf8Ldd9zfEve5cHce97PEfSy0g7sX4n4H7qm5ucj3yaD3DUW+z4d23Vjk+3Rox/VFvk8IPbmLKO434i4c7kqJ+1G4l4a7SuL+EnTlrpS4f+Vy6Rr30VyhtsT9LldJ97gvhrtRuK8i7ru4TnnjvpsbJMd9NejO3TJx/wz3+HB/TNwnc5vKjvtn7lDdcf/M3dI17n+hHdzfEfd7zJIucd8G4XOKfL8Fdytwd0Lch8DZjZyFGOcl8pez7eL8Os4x5Ky4OI/vaclxfh/nEHL+XJxXRz7Ob4vzH59XXJx3Rz7OX4vz2F6WHOe1cc4cZ5vF+Wfk42yxOE/sNcXFeWjUxdlXcX4W5XBeV5zfRb7Pinw+FmVzFlecv/Wu0sb5YJTL+VdxHtYHkuP8LPJyVlOcz0S9nE8T59VQLudFxflSCyXHeVLUw3lGcX4RunFWUpy3RD2c/RPn+VAXZxXF+URfK2+cl0RdnN0T5/Og159FPs+HejmPKM4rWqSy4/ygf+ot83kzpEOI84doG3Fx/gxlcf5NnF+DXpwNE+fLoAfn4cR5OehCXJw3g96chxLno6AHZ8HEeTH8j/NZ4vyWUmnjfBXqbVHm816om7M34jwO6uZ8kThPhHpXLPN5JdTDeSlxvkojyXG+Cu3krII4vwDdOD8kzhdBr5ZlPp+Es1XYDx/76dGNszniPA705iyFOF8BvdYu8/kd6NaqzOdfoBtnTcT5E+jF+RBx3gN6dCjzeRTowtkacV4HduhU5vMzaEe/Mu/fR6+OZT6PA702KvP5DOjG+QVxXgH1bljm8yCoh/MU4jwG9OxR5vMtaEevMp+P0EFp4zwG6uYsgNjfj67s94794tiR/bdxPg16DCrz+QGcazC8zPvN0YW9/LG/H13Yvx771dGdveCxvxs92I8f++3RtX+Z989jC/ZKx/5o9NyizOcFYEv2hsb+0f7SPfa3U+5WZd5Pj+7s94793eg5qsznBaDn6DLvV0ePsWXeP47eO5R5/zZtZ69x7EdGN/Zmx35s9N6rzPtXqYu907EfGt3YPxz7kdGb/amxvxVd2Fsb+23Rm/3AO4m3kxz7hccqb+xnRY/dy7xfm75kr1/sF6Qt7FWN/anotU+Z9z9j1xPKvD8QPQ8o835f2s1eydg/OVly7JdE70PKvB8WXdi/Gfs5aQt7SWP/KbZi/1/sD6Qdx5Z5vym6sfc19sfS7mPKvF+UdpxS5v2E6MpeyePEB6nu2C9KOaeWeT8lurJ3MfYr0jb2gsV+L+zG3pjYv47e7NWL/XnHSI79fOjOfrzYf4ceZ5V5fyR2ml7m/XvYmr1JV4mxwzVl3q+EXuyfi/12tIO9irE/8RTFxX66UxUX+x2pm/1msb+MvOyXi/10pGMvWewfo23sVYr9S7Tj1jLvX6Kd7OeK/V60hb02sb/mItUV++EuVtrYP4ae7O+J/ULY+b4y79e5TLrE/jTs8miZ96egN3uvYv/WNSor9htdq7jYr3Wd8sZ+F/Rif0rsR6Et7N+I/Rm0+/Ey7++g7ezNif046MV+lNivQrvY3xP7g+6UHPuH0IP9I7EfBTs9Veb9PjOlS+yvoR3sd4j9EA+qrtgvQ13s5Yj9HtTzdJn3q8xWXbHfBb3ZjxH7NbAl66tjfTbtnlfm/SGPK23s98BurCeO9cnozt6E2H+A3h+Ueb05urBXIvZPoDdr/2N/AHq/V+b9FLTzmzKv/0Zv9hvE/oQXVVfsf3hJdcV6dvZWsPY01v+/KjnW+9MO1n/H+nD0+rTM+yGo5/My709Az+/KvL4dXVnrH/sBsNuvZV5//ZHKjvXk6Ml66FhfTV2sF4/14NTF+uZYD/2F0sb6aur5uczrzf9pZy2vb8VWyLG+lXayFjjW+6I765djfTP1sl461lejJ2uNY/3xYuWN9cHUTVysV0ZP1j/H+mnaznrBWD+I3qx/jfWx6MJa3lj/ix6sFY31pBWljfWz6Mb611gfWyptrE+lnaxHjPWM6NW8ltfPojfrR2P9KbqynjPWbzZUXKxHRS/WG8b6QvRgPWasp0SP1Wt5/WhzxcX6y2VVdqwnbaGyYv0ZerPeLdbDUS9rDWP9YUvJsX5xVaWN9XbUzfq+WL9Hve1ref0f9bJ+LNabUTZr12K9GuWyPi7W162jtLGejHK71fL6NNYashYo1g+1V95Yf4defWt5vRBlsz4s1o9R74a1vH6MfKynivVY1MXapVjPhB6s/4n1Q5QzoJbXY5Fvk1pe79RXaWN9EeUMquX1RORlbU2sz2Fd1pBaXm9DWaw9ifUo5GX9R6wXoVzWbsR6DcoZWcvrVcg3qpbXm5Bv61pe70Fa1lfEegnWqYyp5fUX5GVtQKwXIC//nh//3k++cbW8foB042t5fQDrFvi38/j39HGS49/bScu/Lce/RxM+UWEw4fx7MP9G/H9QSwECFAMUAAAACADEgX1XBUjZfkMqAABgjAAAJQAAAAAAAAAAAAAAgAEAAAAAZGF0YS9mMjI3NWViMDkyY2FjNDg5MjkxMGM3NDVlYmUxY2ExNlBLBQYAAAAAAQABAFMAAACGKgAAAAA=\"},\"axes\":{\"id\":\"1006\"},\"margin\":[5,5,5,5],\"orientation_widget\":true,\"scene\":{\"calls\":[[\"addRenderer\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b23fadd110}\"]],[\"addRenderer\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b23fad6bf0}\"]],[\"addRenderer\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427c2430}\"]]],\"dependencies\":[{\"calls\":[[\"setActiveCamera\",[\"instance:${000055b23fad8e90}\"]],[\"addViewProp\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427ce860}\"]]],\"dependencies\":[{\"id\":\"000055b23fad8e90\",\"parent\":\"e89ba130-de3e-4a59-b4e7-b6c32865706d000055b23fadd110\",\"properties\":{\"clippingRange\":[4.297922728408016,14.247216514350688],\"focalPoint\":[1.4999999999999998,1.5,0.75],\"position\":[6.519097822426849,6.519097822426848,5.769097822426848],\"viewUp\":[0.0,0.0,1.0]},\"type\":\"vtkOpenGLCamera\"},{\"calls\":[[\"setMapper\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427cbeb0}\"]],[\"setProperty\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427cf9f0}\"]]],\"dependencies\":[{\"calls\":[[\"setInputData\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427cbeb0-dataset-0}\",0]],[\"setLookupTable\",[\"instance:${e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427cc8e0}\"]]],\"dependencies\":[{\"id\":\"e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427cbeb0-dataset-0\",\"parent\":\"e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427cbeb0\",\"properties\":{\"fields\"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"viewUp\":[0.0,0.0,1.0]},\"type\":\"vtkOpenGLCamera\"}],\"id\":\"e89ba130-de3e-4a59-b4e7-b6c32865706d000055b2427c2430\",\"parent\":\"e89ba130-de3e-4a59-b4e7-b6c32865706d000055b23fadec60\",\"properties\":{\"background\":[0.0,0.0,0.0],\"background2\":[0.2,0.2,0.2],\"clippingRangeExpansion\":0.5,\"interactive\":0,\"layer\":1,\"lightFollowCamera\":1,\"maximumNumberOfPeels\":4,\"nearClippingPlaneTolerance\":0.001,\"occlusionRatio\":0.0,\"preserveColorBuffer\":1,\"preserveDepthBuffer\":0,\"twoSidedLighting\":1,\"useDepthPeeling\":0,\"useShadows\":0,\"viewport\":[0.0,0.0,0.2,0.2]},\"type\":\"vtkOpenGLRenderer\"}],\"id\":\"e89ba130-de3e-4a59-b4e7-b6c32865706d000055b23fadec60\",\"mtime\":21600,\"parent\":\"e89ba130-de3e-4a59-b4e7-b6c32865706d0x0\",\"properties\":{\"numberOfLayers\":2},\"type\":\"vtkXOpenGLRenderWindow\"},\"sizing_mode\":\"stretch_width\"},\"id\":\"1007\",\"type\":\"panel.models.vtk.VTKSynchronizedPlot\"},{\"attributes\":{},\"id\":\"1006\",\"type\":\"panel.models.vtk.VTKAxes\"},{\"attributes\":{\"client_comm_id\":\"270b7091a2644597aba018ae9dce0f61\",\"comm_id\":\"6751851446214a7bbb036bcc7e54ef84\",\"plot_id\":\"1007\"},\"id\":\"1008\",\"type\":\"panel.models.comm_manager.CommManager\"}],\"root_ids\":[\"1007\",\"1008\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.3\"}};\n",
       "    var render_items = [{\"docid\":\"41cbf894-c2c7-4877-9e5a-bd18fb34f3e0\",\"root_ids\":[\"1007\"],\"roots\":{\"1007\":\"9f4bc3cf-69c7-4577-aa6b-b5b542c17b7a\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['vtk'] !== undefined) && ( root['vtk'] !== undefined) && ( root['vtk'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['vtk'] !== undefined) && (root['vtk'] !== undefined) && (root['vtk'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "VTKRenderWindowSynchronized(vtkXOpenGLRenderWindow, orientation_widget=True, sizing_mode='stretch_width')"
      ]
     },
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1007"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pv.set_jupyter_backend('panel')\n",
    "pv.start_xvfb()\n",
    "mesh_pv = pv.read(new_mesh)\n",
    "mesh_pv.plot(show_edges=True, color=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "顶部出口附近的网格：\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/113e854970e349d89e5faef091a9dd8e679e8f3ed6684656bc6c1f56002575dc)\n",
    "\n",
    "侧壁入口附近的网格：\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/84c8fa0573894b56aef6ce604c009cf991792ce1ee5148908c8831ba416ce0f7)\n",
    "\n",
    "可以明显地看到，**我们的自适应策略主要对房间的出入口区域附近的区域进行了网格加密**，这较为符合物理直觉："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**至此，我们完成了一轮完整的PINNs指导的从level1 → level2的网格加密流程。**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "之后的不同网格层级之间的加密均采用此细化策略。所有代码和文件均在work文件夹中，此处不详细展开。**注意，代码生成的网格.vtk文件仍然需要使用gmsh将其转化为.bdf文件，然后再导入Workbench中设置边界类型供Fluent计算**。\n",
    "\n",
    "\n",
    "综上，按照以上思路和流程，我们总共对室内空气流动的原网格Level1 → Level2 → Level3 → Level4 → Level5 **进行了四轮网格加密**，最终通过交线速度幅值的对比与分析，认为Level4的网格为最优网格。\n",
    "\n",
    "\n",
    "**详细的交线速度幅值的最大值和分布将在下一节中进行展示**。\n",
    "\n",
    "\n",
    "#### 1. 以下是室内流动不同的优化Level所对应的出口附近的网格：\n",
    "\n",
    "#### Level1（1,479 Points，7,010 Cells）\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/b3844ab4dae549488d6bb0e3fc4547c1748caa9d9ccc4b98858ecae8519366f3)\n",
    "\n",
    "#### Level2（3,242 Points，16,174 Cells）\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/c44460e62a0e401a8524dd7a7d7933f867c64d6bb49a4ec8957d40030768ca8f)\n",
    "\n",
    "#### Level3（6,792 Points，34,729 Cells）\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/94347396839f4a75a846ab5f674cd6783261127bc4934ef2aaf107723c30d664)\n",
    "\n",
    "#### Level4（10,856 Points，54,847 Cells）\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/1aacf431f99c4448bffc7ca4f30c64458ba462e005d14c5fad48d4fc872fd30a)\n",
    "\n",
    "#### Level5（19,155 Points，95,993 Cells）\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/d55a52666c2241788b4fd45cc98f36c0c82d4978b45c42ca9032fbc2bdc7c61b)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 三. 验证最优网格\n",
    "\n",
    "#### 1.Fluent自适应网格加密设置\n",
    "\n",
    "考虑到结果的准确性，所以**采用了Fluent自带的自适应网格加密方法作为参考和对比**。自适应网格加密方法可以手动设置，这个案例中设置基于压力Hessian矩阵的变化来自适应网格加密，选择预定义标准——Pressure-hessian，对细化标准以及粗化标准也可以自己定义，需要注意设置好合适的频率（迭代），结果收敛后再进行下一次的自适应网格加密。\n",
    "\n",
    "\n",
    "对原网格一共进行了**4次**自适应网格加密，最后得到了230020个网格，自适应加密后的网格可以看到其也对房间出入口附近区域的网格加密比较明显，并且改变了原有四面体网格的几何属性，细化成了多面体网格，导致在某些地方的网格连接很混乱。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/c4594eb3c20e4efa8375f16848d6dcdd131a836ee469450f81f2d48568cba0ac)\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/de0a22c0e8c04e93bbce04ee9fdffa56e6f59544f8fe46f0a1ba0665e25e2913)\n",
    "\n",
    "\n",
    "\n",
    "对每次自适应加密后的网格按照与原网格一样的边界条件进行模拟，依次得到了每次加密后的流场，将其与基于Edges中点的网格细化算法加密后的沿着y方向的交线速度幅值的最大值进行对比。如下图所示，结果表明我们的基于Edges中点的网格细化算法以及fluent自适应加密算法，均会使得速度幅值的最大值随着网格加密即网格数量的增加趋向于收敛。值得注意的是，**Fluent自适应三维网格加密是将一个四面体网格分为四个多面体网格；而我们的网格细化算法是将一个四面体网格分为八个四面体网格，不但保证了网格的几何属性始终一致，并且适应性也很好。尽管网格细化一次后单元的数量上相比与Fluent更多，但最终也可以很快地达到与Fluent加密网格相同的收敛水平**。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/7864cb9a06774fbfbc4f1c329e7ac4e4f381e328b1fe4d1eaf3e827b30066aba)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. 网格结果定量分析\n",
    "\n",
    "接下来我们对最优网格进行敏感性分析，即将最优网格（Level4）进行网格数目的加倍和减半，再对比CFD结果的变化情况来判定网格的优劣。根据与Fluent自适应网格加密的结果对比，得到了基于Edges中点的网格细化算法下的最优网格，并对比最优网格网格数加倍（level5）与减半（level2）处理，分别定义为网格N0（减少），N1（最优网格）和N2（增加）。\n",
    "\n",
    "#### 网格N0：\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/c44460e62a0e401a8524dd7a7d7933f867c64d6bb49a4ec8957d40030768ca8f)\n",
    "\n",
    "#### 网格N1：\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/1aacf431f99c4448bffc7ca4f30c64458ba462e005d14c5fad48d4fc872fd30a)\n",
    "\n",
    "#### 网格N2：\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/d55a52666c2241788b4fd45cc98f36c0c82d4978b45c42ca9032fbc2bdc7c61b)\n",
    "\n",
    "我们分别计算了这三种网格的交线速度最大值情况，得到的结果显示网格N1与网格数增加接近两倍的网格N2速度最大值几乎相同，差异<0.02%；而N1与网格数减小两倍多的网格N0的速度最大值对比差异在9%左右，可以证明N1为最优网格。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/c739c77378444a8d971fbe0420a4ca92426ab0f94fc5407babb32c655b3c7fe8)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3. 网格结果定性分析\n",
    "\n",
    "同时可以得到交线上的速度分布，将得到的网格N1（最优网格）与网格N0（减少）和网格N2（增加）的速度分布进行定性对比，会发现**N1与N2的速度分布区别很小**，在最大值处完全一致；**而N1与N0的速度分布在出口处也是最大值处比较明显**。若将三种网格放在一起对比会更明显看到网格N0与网格N1, N2的压力分布的区别。\n",
    "\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/7d9620b0f73f4406b6b396afaca6a43335c2087d192440d99a2d44ca01083638)\n",
    "![](https://ai-studio-static-online.cdn.bcebos.com/578ea5d7b48a4690b0532d3803fa641dd40aab999c784995aa13024764612122)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "请点击[此处](https://ai.baidu.com/docs#/AIStudio_Project_Notebook/a38e5576)查看本环境基本用法.  <br>\n",
    "Please click [here ](https://ai.baidu.com/docs#/AIStudio_Project_Notebook/a38e5576) for more detailed instructions. "
   ]
  }
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